Title of article :
Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices
Author/Authors :
Wang، نويسنده , , Cheng-Li Tong، نويسنده , , Tiejun and Cao، نويسنده , , Longbing and Miao، نويسنده , , Baiqi، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2014
Pages :
11
From page :
222
To page :
232
Abstract :
In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is non-parametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the prior information on the population covariance matrix. Analytical results on the improvement of the proposed shrinkage estimator are provided and some corresponding asymptotic properties are also derived. Finally, we demonstrate the practical improvement of the proposed method over existing methods through extensive simulation studies and real data analysis.
Keywords :
High-dimensional data , Shrinkage estimator , Large p small n , U -statistic
Journal title :
Journal of Multivariate Analysis
Serial Year :
2014
Journal title :
Journal of Multivariate Analysis
Record number :
1566645
Link To Document :
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